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KDD-2005 Call for Industrial/Government Track Papers
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The Eleventh ACM SIGKDD International Conference
on Knowledge Discovery and Data Mining
August 21-24, 2005
Chicago, IL, USA
http://www.acm.org/sigkdd/kdd2005http://www.kdd2005.com
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Areas of Interest:
The Industrial/Government Track of the Eleventh ACM SIGKDD International
Conference on Knowledge Discovery and Data Mining will highlight
successful applications of KDD technology; explore issues, methods,
and lessons learned in the development and deployment of KDD
applications; and promote the exchange of ideas between basic
and applied data mining.
The KDD-2005 Industrial/Government (I/G) Track seeks to: (1)
provide a forum for exchanging ideas between KDD practitioners,
researchers, companies, and government organizations; and (2)
help commercial and government organizations understand successful
KDD applications. The I/G Track solicits papers from practitioners
and companies that have KDD products and solutions relevant to
commercial or government challenges.
The I/G Track will consist of competitively-selected contributed
papers - presented in oral and poster form - as well as invited
talks and panel discussions. (The full conference will also
feature keynote presentations, workshops, tutorials, research
track papers, and the KDD Cup competition.)
We envision submissions along three sub-areas: (1) emerging
applications, technology, and issues; (2) deployed KDD case studies;
and (3) Products. Emerging application, technology, and issue
papers discuss prototype applications, tools for focused domains
or tasks, useful techniques or methods, project "war stories",
useful system architectures, scalability enablers, tool evaluations,
or integration of KDD and other technologies. Case studies describe
deployed projects with measurable benefits that include KDD technology.
Product submissions clearly describe KDD technology embedded
in commercial products (without otherwise being a product advertisement).
Submitters are encouraged (but not required) to select one (or
more) of these sub-areas for their papers.
In their submission, authors are encouraged to explain why the
application is important, the specific need for KDD technology
to solve the problem (including why other methods may fall short),
and any innovations or lessons learned in the solution. We understand
that reasons of confidentiality have often discouraged practitioners
from submitting papers. When possible, we encourage authors
to abstract any such specifics into a more general problem that
may be presented, while explaining how the abstracted challenge
is important for KDD.
Submission Guidelines:
Electronic Abstract Submission: Feb. 18, 2005 *at noon CST*
Electronic Paper Submission: Feb. 28, 2005 *at noon CST*
Notification of acceptance/rejection: May 20, 2005
Camera-ready papers due: June 3, 2005
Abstracts and full papers must be submitted electronically at the
conference Web site (see URL above). Abstracts must be submitted on or
before February 18, 2005, 12 noon CST (Central Standard Time). An abstract
may not contain more than 250 words. No paper will be considered without
having the abstract submitted on time. Full papers must be submitted on or
before February 28, 2005, at 12 noon CST. This is a FIRM deadline. Papers
must be no more than 10 pages in length, inclusive of all figures, tables,
references and appendices. Papers should be submitted in ACM proceedings
format (two columns, 9pt font, approx. 1in margins). Templates are
available at http://www.acm.org/sigs/pubs/proceed/template.html. Papers
must be submitted in PDF format. Authors are solely responsible for
ensuring that their submissions display and print properly.
All papers will be judged based on their technical merits, originality,
relevance to KDD, and presentation clarity. Papers should describe original
work that has not been published before, is not under review elsewhere, and
may not be submitted elsewhere during KDD-2005's review period (specialized
workshops with a limited audience excluded).
I/G Track Program Co-Chairs:
Corinna Cortes, Google Inc, USA
Jaideep Srivastava, University of MN, USA
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